The advent of global communications networks (e.g. the Internet) now makes accessible an enormous amount of data. People access and query unstructured and structured data every day. Unstructured data is used for creating, storing and retrieving reports, e-mails, spreadsheets and other types of documents, and consists of any data stored in an unstructured format at an atomic level. In other words, in the unstructured content, there is no conceptual definition and no data type definition—in textual documents, a word is simply a word. Current technologies used for content searches on unstructured data require tagging entities such as names or applying keywords and metatags. Therefore, human intervention is required to help make the unstructured data machine readable. Structured data is any data that has an enforced composition to the atomic data types. Structured data is managed by technology that allows for querying and reporting against predetermined data types and understood relationships.
Programming languages continue to evolve to facilitate specification by programmers as well as efficient execution. In the early days of computer languages, low-level machine code was prevalent. With machine code, a computer program or instructions comprising a computer program were written with machine languages or assembly languages and executed by the hardware (e.g., microprocessor). These languages provided an efficient means to control computing hardware, but were very difficult for programmers to comprehend and develop sophisticated logic.
Subsequently, languages were introduced that provided various layers of abstraction. Accordingly, programmers could write programs at a higher level with a higher-level source language, which could then be converted via a compiler or interpreter to the lower level machine language understood by the hardware. Further advances in programming have provided additional layers of abstraction to allow more advanced programming logic to be specified much quicker then ever before. However, these advances do not come without a processing cost.
The state of database integration in mainstream programming languages leaves a lot to be desired. Many specialized database programming languages exist, such as xBase, T/SQL, and PL/SQL, but these languages have weak and poorly extensible type systems, little or no support for object-oriented programming, and require dedicated run-time environments. Similarly, there is no shortage of general purpose programming languages, such as C#, VB.NET, C++, and Java, but data access in these languages typically takes place through cumbersome APIs that lack strong typing and compile-time verification. In addition, such APIs lack the ability to provide a generic interface to query data, data collections, and the like.